Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

doi:10.3390/rs12030492

	Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation
	Li, Lianfa 1,2
刊名	REMOTE SENSING
	2020-02-01
卷号	12 期号:3 页码:20
关键词	parameter inversion aerosol optical depth PBLH ground-based AOD PM2 5 automatic differentiation
DOI	10.3390/rs12030492
通讯作者	Li, Lianfa(lilf@lreis.ac.cn)
英文摘要	Satellite aerosol optical depth (AOD) plays an important role for high spatiotemporal-resolution estimation of fine particulate matter with diameters <= 2.5 mu m (PM2.5). However, the MODIS sensors aboard the Terra and Aqua satellites mainly measure column (integrated) AOD using the aerosol (extinction) coefficient integrated over all altitudes in the atmosphere, and column AOD is less related to PM2.5 than low-level or ground-based aerosol (extinction) coefficient (GAC). With recent development of automatic differentiation (AD) that has been widely applied in deep learning, a method using AD to find optimal solution of conversion parameters from column AOD to the simulated GAC is presented. Based on the computational graph, AD has considerably improved the efficiency in applying gradient descent to find the optimal solution for complex problems involving multiple parameters and spatiotemporal factors. In a case study of the Jing-Jin-Ji region of China for the estimation of PM2.5 in 2015 using the Multiangle Implementation of Atmospheric Correction AOD, the optimal solution of the conversion parameters was obtained using AD and the loss function of mean square error. This solution fairly modestly improved the Pearson's correlation between simulated GAC and PM2.5 up to 0.58 (test R-2: 0.33), in comparison with three existing methods. In the downstream validation, the simulated GACs were used to reliably estimate PM2.5, considerably improving test R-2 up to 0.90 and achieving consistent match for GAC and PM2.5 in their spatial distribution and seasonal variations. With the availability of the AD tool, the proposed method can be generalized to the inversion of other similar conversion parameters in remote sensing.
资助项目	Strategic Priority Research Program of Chinese Academy of Sciences[XDA19040501] ; National Natural Science Foundation of China[41471376]
WOS关键词	PARTICULATE MATTER ; PM2.5 CONCENTRATIONS ; POLLUTION ; DISTRIBUTIONS ; VARIABILITY ; TRANSPORT ; CHINA ; HAZE ; NO2
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000515393800151
资助机构	Strategic Priority Research Program of Chinese Academy of Sciences ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/132859]
专题	中国科学院地理科学与资源研究所
通讯作者	Li, Lianfa
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Datun Rd, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Li, Lianfa. Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation[J]. REMOTE SENSING,2020,12(3):20.
APA	Li, Lianfa.(2020).Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation.REMOTE SENSING,12(3),20.
MLA	Li, Lianfa."Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation".REMOTE SENSING 12.3(2020):20.